Message brokering across different systems, with transactionality and the ability to have fine tuned control over what happens using Java (or other languages), instead of a heavy, proprietary languages. One situation that it doesn't fit very well (as far as I have experienced) is when your workflow requires significant data mapping. While possible when using Java tooling, some other visual data mapping tools in other integration frameworks are easier to work with.
If you want to stream high volumes of data, be it for ETL streaming or event sourcing, Google Cloud Pub/Sub is your go-to tool. It's easy to learn, easy to observe its metrics and scales with ease without additional configuration so if you have more producers of consumers, all you need to do is to deploy on k8s your solutions so that you can perform autoscaling on your pods to adjust to the data volume. The DLQ is also very transparent and easy to configure. Your code will have no logic whatsoever regarding orchestrating pubsub, you just plug and play. However, if you are not in the Google Cloud Pub/Sub environment, you might have trouble or be most likely unable to use it since I think it's a product of Google Cloud.
If you’re bringing anything into Salesforce you should just invest now into Mule, you will get your money’s worth and find a myriad of uses to build APIs between many other systems. Once you build a component you can easily reuse it as a building block to attach to another source/destination. This makes it easy to ramp up quickly and spread usage of Mule throughout your enterprise. A good value for medium to large companies, but probably cheaper to outsource your job to a consulting firm if you are smaller.
Camel has an easy learning curve. It is fairly well documented and there are about 5-6 books on Camel.
There is a large user group and blogs devoted to all things Camel and the developers of Camel provide quick answers and have also been very quick to patch Camel, when bugs are reported.
Camel integrates well with well known frameworks like Spring, and other middleware products like Apache Karaf and Servicemix.
There are over 150 components for the Camel framework that help integrate with diverse software platforms.
With a pub/sub architecture the consumer is decoupled in time from the publisher i.e. if the consumer goes down, it can replay any events that occurred during its downtime.
It also allows consumer to throttle and batch incoming data providing much needed flexibility while working with multiple types of data sources
A simple and easy to use UI on cloud console for setup and debugging
It enables event-driven architectures and asynchronous parallel processing, while improving performance, reliability and scalability
It is best suited for Rest API development. Mule ESB uses RAML as an API descriptor which is less complex and easy to understand. RAML is an open standard majorly supported by Mulesoft. Once RAML is developed, it is very easy (a few clicks)to create flows corresponding to the resources defined in the RAML. One can also include JSON schema validation in RAML, and with the use of APIkit router, Mule ESB makes the request validation very easy (it's automatic basically.)
Mule ESB comes with a large spectrum of community and enterprise connectors. We have connectors for all the major platforms like Facebook, Twitter, Salesforce, SAP, etc. This enables Mule ESB to integrate with the other systems in a faster and more robust way. Mule ESB has many components to fulfill the requirements of each integration (for example batch processing, parallel processing, choice, etc.)
Mule API gateway is one of the best tools (modules) of Mulesoft's offering. It supports API governance and management very well. One can easily enforce policies on their APIs with API gateway. It enables some of the must-have features in an API solution (i.e. throttling, oAuth, access levels, etc.)
Implementing a CI/CD (DevOps) environment for Mule ESB is a very easy task. Mule majorly uses MAVEN as its build tool, which in turn makes it best suitable for CI/CD approach. Mule also provides MAVEN plugins for auto deployments to the servers. Mule also has a best Unit testing module which is MUnit. MUnit can be used for both Unit and Functional testing, and it is easy to write and generates coverage reports in various formats.
It serves all of our purposes in the most transparent way I can imagine, after seeing other message queueing providers, I can only attest to its quality.
It is easy to create Google Cloud Pub/Sub topics from both Web Console and CLI commands.
Google Cloud Pub/Sub supports creation of one or more subscriptions.
By supporting a BigQuery Pub/Sub subscription to automatically write to a BigQuery table it simplifies development by avoiding implementation of a custom micro service for writes to BigQuery.
They have decent documentation, but you need to pay for support. We weren't able to answer all our questions with the documentation and didn't have time to setup support before we needed it so I can't give it a higher rating but I think it tends to be a bit slow unless you're a GCP enterprise support customer.
If you are looking for a Java-based open source low cost equivalent to webMethods or Azure Logic Apps, Apache Camel is an excellent choice as it is mature and widely deployed, and included in many vendored Java application servers too such as Redhat JBoss EAP. Apache Camel is lacking on the GUI tooling side compared to commercial products such as webMethods or Azure Logic Apps.
Having used Amazon Web Services SNS & SQS I can say that even if the latter may offer more features, Google Cloud Pub/Sub is easier to use. On the other hand, usage of SNS & SQS as well as documentation and troubleshooting is easier with the AWS solution. Since we are not using GCP only for Pub/Sub the choice depends on other variables.
You can just plug in consumers at will and it will respond, there's no need for further configuration or introducing new concepts. You have a queue, if it's slow, you plug in more consumers to process more messages: simple as that.
Very fast time to market in that so many components are available to use immediately.
Error handling mechanisms and patterns of practice are robust and easy to use which in turn has made our application more robust from the start, so fewer bugs.
However, testing and debugging routes is more challenging than working is standard Java so that takes more time (less time than writing the components from scratch).
Most people don't know Camel coming in and many junior developers find it overwhelming and are not enthusiastic to learn it. So finding people that want to develop/maintain it is a challenge.
